Pandas Profiling Report

Dataset statistics

Number of variables	39
Number of observations	10324
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	104
Duplicate rows (%)	1.0%
Total size in memory	3.1 MiB
Average record size in memory	312.0 B

Variable types

Numeric	8
Categorical	31

Alerts

Dataset has 104 (1.0%) duplicate rows	Duplicates
`Line Item Quantity` is highly correlated with `Line Item Value` and 3 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price` and 1 other fields	High correlation
`Unit Price` is highly correlated with `Pack Price` and 3 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Unit Price` and 4 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit Price` and 4 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Pack Price` and 5 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 2 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price`	High correlation
`Unit Price` is highly correlated with `Pack Price`	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Weight (Kilograms)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_HRDT` and 3 other fields	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_HRDT` is highly correlated with `Sub Classification_Adult` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM`	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Product Group_ARV` is highly correlated with `Sub Classification_Adult` and 3 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Product Group_HRDT` and 5 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Vendor INCO Term_EXW` and 2 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Vendor INCO Term_EXW` and 2 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Sub Classification_Adult` and 3 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Vendor INCO Term_EXW` and 2 other fields	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Product Group_ACT` and 4 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_Ethiopia Field Office` is highly correlated with `Managed By_Haiti Field Office`	High correlation
`Managed By_Haiti Field Office` is highly correlated with `Managed By_Ethiopia Field Office`	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 6 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 8 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Vendor INCO Term_DDP` and 2 other fields	High correlation
`Shipment Mode_Truck` is highly correlated with `Vendor INCO Term_EXW` and 1 other fields	High correlation
`Product Group_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ARV` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Sub Classification_Adult` is highly correlated with `Vendor INCO Term_EXW` and 4 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Unit of Measure (Per Pack)` and 2 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Unit Price` is highly skewed (γ1 = 40.58598947)	Skewed
`Weight (Kilograms)` is highly skewed (γ1 = 34.05916463)	Skewed

Reproduction

Analysis started	2022-05-21 11:59:29.688515
Analysis finished	2022-05-21 11:59:49.413232
Duration	19.72 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Unit of Measure (Per Pack)
Real number (ℝ)

HIGH CORRELATION

Distinct	31
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.943316949 × 10^-17

Minimum	-1.005417359
Maximum	12.0404362
Zeros	0
Zeros (%)	0.0%
Negative	7526
Negative (%)	72.9%
Memory size	80.8 KiB

Quantile statistics

Minimum	-1.005417359
5-th percentile	-0.7572980217
Q1	-0.6267088971
median	-0.234941523
Q3	0.156825851
95-th percentile	2.115662721
Maximum	12.0404362
Range	13.04585356
Interquartile range (IQR)	0.7835347481

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	3.397691963 × 10¹⁶
Kurtosis	36.09399876
Mean	2.943316949 × 10^-17
Median Absolute Deviation (MAD)	0.391767374
Skewness	4.302502487
Sum	0
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
-0.234941523	4121	39.9%
-0.6267088971	2630	25.5%
0.2874149757	976	9.5%
2.115662721	670	6.5%
0.548593225	474	4.6%
-0.7572980217	470	4.6%
0.156825851	222	2.2%
2.899197469	157	1.5%
-1.005417359	126	1.2%
-0.6920034594	114	1.1%
Other values (21)	364	3.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1.005417359	126	1.2%
-0.9923584462	4	< 0.1%
-0.9792995337	8	0.1%
-0.9531817088	4	< 0.1%
-0.8617693215	2	< 0.1%
-0.7834158467	4	< 0.1%
-0.7572980217	470	4.6%
-0.7050623719	2	< 0.1%
-0.6920034594	114	1.1%
-0.6267088971	2630	25.5%

Value	Count	Frequency (%)
12.0404362	16	0.2%
8.383940706	5	< 0.1%
6.033336461	7	0.1%
3.369318318	39	0.4%
2.899197469	157	1.5%
2.507430095	53	0.5%
2.115662721	670	6.5%
1.593306222	76	0.7%
1.332127973	76	0.7%
1.175421023	3	< 0.1%

Line Item Quantity
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5065
Distinct (%)	49.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.607138961 × 10^-17

Minimum	-0.4579064323
Maximum	15.02912585
Zeros	0
Zeros (%)	0.0%
Negative	7833
Negative (%)	75.9%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.4579064323
5-th percentile	-0.4575067657
Q1	-0.4477399122
median	-0.3829939168
Q3	-0.03229268645
95-th percentile	1.813962354
Maximum	15.02912585
Range	15.48703228
Interquartile range (IQR)	0.4154472258

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	1.513587712 × 10¹⁶
Kurtosis	40.0503001
Mean	6.607138961 × 10^-17
Median Absolute Deviation (MAD)	0.07368853644
Skewness	5.038314699
Sum	6.536993169 × 10^-13
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.2081397625	93	0.9%
-0.4329522466	91	0.9%
-0.455433495	87	0.8%
-0.4079730817	73	0.7%
-0.333035587	69	0.7%
-0.445441829	67	0.6%
0.04165188644	67	0.6%
-0.3829939168	66	0.6%
-0.457856474	63	0.6%
0.7910268333	62	0.6%
Other values (5055)	9586	92.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.4579064323	35	0.3%
-0.4578814532	40	0.4%
-0.457856474	63	0.6%
-0.4578314948	46	0.4%
-0.4578065157	28	0.3%
-0.4577815365	48	0.5%
-0.4577565573	27	0.3%
-0.4577315782	26	0.3%
-0.457706599	22	0.2%
-0.4576816198	54	0.5%

Value	Count	Frequency (%)
15.02912585	1	< 0.1%
14.55219865	1	< 0.1%
13.410426	1	< 0.1%
12.40633851	3	< 0.1%
12.39449839	1	< 0.1%
11.03350859	1	< 0.1%
10.53290114	1	< 0.1%
10.49315929	1	< 0.1%
9.582718689	1	< 0.1%
9.533734547	2	< 0.1%

Line Item Value
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	8754
Distinct (%)	84.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-6.469490233 × 10^-17

Minimum	-0.4566811858
Maximum	16.78221805
Zeros	0
Zeros (%)	0.0%
Negative	7651
Negative (%)	74.1%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.4566811858
5-th percentile	-0.4560855913
Q1	-0.444015585
median	-0.3683149727
Q3	0.02540381669
95-th percentile	1.57894586
Maximum	16.78221805
Range	17.23889923
Interquartile range (IQR)	0.4694194017

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	-1.545791706 × 10¹⁶
Kurtosis	54.15746236
Mean	-6.469490233 × 10^-17
Median Absolute Deviation (MAD)	0.08674285175
Skewness	5.837353819
Sum	-5.684341886 × 10^-13
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.1225838077	29	0.3%
-0.4103400129	23	0.2%
-0.4543641546	18	0.2%
-0.4149741331	16	0.2%
0.2506477188	15	0.1%
-0.4474129744	15	0.1%
-0.1091222013	13	0.1%
-0.4559571334	11	0.1%
-0.4534373306	11	0.1%
-0.3408282102	11	0.1%
Other values (8744)	10162	98.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.4566811858	1	< 0.1%
-0.4566811278	1	< 0.1%
-0.4566808672	1	< 0.1%
-0.4566806355	1	< 0.1%
-0.4566805196	1	< 0.1%
-0.4566804906	1	< 0.1%
-0.4566799983	1	< 0.1%
-0.4566797666	1	< 0.1%
-0.4566791873	1	< 0.1%
-0.4566787818	1	< 0.1%

Value	Count	Frequency (%)
16.78221805	1	< 0.1%
16.25134251	1	< 0.1%
14.98041651	1	< 0.1%
14.43076219	1	< 0.1%
13.90689587	1	< 0.1%
11.93632275	1	< 0.1%
11.79080523	1	< 0.1%
11.16916779	1	< 0.1%
10.93421789	1	< 0.1%
10.85057202	2	< 0.1%

Pack Price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION

Distinct	1185
Distinct (%)	11.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.752974567 × 10^-17

Minimum	-0.4808215048
Maximum	29.02243684
Zeros	0
Zeros (%)	0.0%
Negative	7591
Negative (%)	73.5%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.4808215048
5-th percentile	-0.4393828045
Q1	-0.3900510184
median	-0.2771360415
Q3	0.03792963217
95-th percentile	1.272978303
Maximum	29.02243684
Range	29.50325834
Interquartile range (IQR)	0.4279806506

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	3.632610509 × 10¹⁶
Kurtosis	293.0774112
Mean	2.752974567 × 10^-17
Median Absolute Deviation (MAD)	0.1440488153
Skewness	12.98494768
Sum	1.98951966 × 10^-13
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.2205668668	368	3.6%
1.272978303	307	3.0%
1.470305447	183	1.8%
-0.235039584	139	1.3%
-0.0425359922	110	1.1%
-0.2889756701	91	0.9%
-0.4382865426	91	0.9%
-0.4275431758	90	0.9%
-0.4349977568	89	0.9%
-0.4314897187	88	0.9%
Other values (1175)	8768	84.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.4808215048	86	0.8%
-0.4724899143	2	< 0.1%
-0.4656930904	2	< 0.1%
-0.4613080427	4	< 0.1%
-0.4572518737	4	< 0.1%
-0.4569229951	2	< 0.1%
-0.4560459856	2	< 0.1%
-0.4553882284	1	< 0.1%
-0.4547304713	1	< 0.1%
-0.4545112189	1	< 0.1%

Value	Count	Frequency (%)
29.02243684	1	< 0.1%
26.92550705	1	< 0.1%
26.76172552	3	< 0.1%
15.96924625	1	< 0.1%
14.86662602	1	< 0.1%
8.289054542	9	0.1%
7.19279263	39	0.4%
6.275659914	3	< 0.1%
6.247376356	3	< 0.1%
6.130076332	1	< 0.1%

Unit Price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	195
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-1.101189827 × 10^-17

Minimum	-0.1842192611
Maximum	72.67010008
Zeros	0
Zeros (%)	0.0%
Negative	8104
Negative (%)	78.5%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.1842192611
5-th percentile	-0.1839902939
Q1	-0.1628489865
median	-0.1384258154
Q3	-0.04378602742
95-th percentile	0.3011912641
Maximum	72.67010008
Range	72.85431934
Interquartile range (IQR)	0.119062959

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	-9.081526273 × 10¹⁶
Kurtosis	2726.111992
Mean	-1.101189827 × 10^-17
Median Absolute Deviation (MAD)	0.03663475662
Skewness	40.58598947
Sum	5.684341886 × 10^-14
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.175060572	720	7.0%
-0.1842192611	517	5.0%
-0.1506374009	464	4.5%
-0.1445316081	445	4.3%
0.05695955329	411	4.0%
-0.1536902973	400	3.9%
0.3011912641	368	3.6%
-0.1720076756	343	3.3%
-0.1384258154	343	3.3%
-0.1292671262	321	3.1%
Other values (185)	5992	58.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.1842192611	517	5.0%
-0.182692813	4	< 0.1%
-0.1811663648	152	1.5%
-0.1796399166	11	0.1%
-0.1781134684	253	2.5%
-0.1765870202	1	< 0.1%
-0.175060572	720	7.0%
-0.1720076756	343	3.3%
-0.1704812274	1	< 0.1%
-0.1689547792	278	2.7%

Value	Count	Frequency (%)
72.67010008	1	< 0.1%
12.53719998	1	< 0.1%
11.26108929	2	< 0.1%
8.971416998	1	< 0.1%
8.028072015	1	< 0.1%
7.444968806	4	< 0.1%
7.39917536	3	< 0.1%
7.292323987	46	0.4%
6.834389529	23	0.2%
5.039286454	3	< 0.1%

Weight (Kilograms)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	3960
Distinct (%)	38.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-3.30356948 × 10^-17

Minimum	-0.3409917532
Maximum	68.18708781
Zeros	0
Zeros (%)	0.0%
Negative	7749
Negative (%)	75.1%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.3409917532
5-th percentile	-0.3393072321
Q1	-0.3238068398
median	-0.2462149573
Q3	-0.001130115975
95-th percentile	1.051757559
Maximum	68.18708781
Range	68.52807956
Interquartile range (IQR)	0.3226767238

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	-3.027175424 × 10¹⁶
Kurtosis	2135.81298
Mean	-3.30356948 × 10^-17
Median Absolute Deviation (MAD)	0.08964130437
Skewness	34.05916463
Sum	-3.801403636 × 10^-13
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.3409118234	55	0.5%
-0.3373949109	48	0.5%
0.5210114987	40	0.4%
-0.3321195421	32	0.3%
-0.3367554722	31	0.3%
-0.3379544197	31	0.3%
-0.3405921041	31	0.3%
-0.3388336478	30	0.3%
-0.3401125251	26	0.3%
-0.3403523146	26	0.3%
Other values (3950)	9974	96.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.3409917532	23	0.2%
-0.3409517883	1	< 0.1%
-0.3409118234	55	0.5%
-0.3408718585	4	< 0.1%
-0.3408318936	20	0.2%
-0.3407519637	19	0.2%
-0.3407119988	2	< 0.1%
-0.3406720339	21	0.2%
-0.340632069	2	< 0.1%
-0.3405921041	31	0.3%

Value	Count	Frequency (%)
68.18708781	1	< 0.1%
22.92618212	1	< 0.1%
16.08474818	1	< 0.1%
12.03046741	1	< 0.1%
8.613227385	3	< 0.1%
6.888261723	2	< 0.1%
6.75357996	5	< 0.1%
6.707940027	1	< 0.1%
6.618898196	2	< 0.1%
6.463194887	1	< 0.1%

Freight Cost (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION

Distinct	6628
Distinct (%)	64.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-3.30356948 × 10^-17

Minimum	-0.6946675877
Maximum	16.21874812
Zeros	0
Zeros (%)	0.0%
Negative	6980
Negative (%)	67.6%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.6946675877
5-th percentile	-0.6530372882
Q1	-0.5576140228
median	-0.3226243468
Q3	0.1608384717
95-th percentile	1.709377804
Maximum	16.21874812
Range	16.91341571
Interquartile range (IQR)	0.7184524945

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	-3.027175424 × 10¹⁶
Kurtosis	30.37207566
Mean	-3.30356948 × 10^-17
Median Absolute Deviation (MAD)	0.2838259114
Skewness	4.337672543
Sum	-5.258016245 × 10^-13
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.1262000273	37	0.4%
-0.2599354609	29	0.3%
-0.3357646137	27	0.3%
-0.6113140284	25	0.2%
-0.1593217799	22	0.2%
-0.2667071931	20	0.2%
-0.149242135	19	0.2%
0.08762951843	18	0.2%
0.5838038598	18	0.2%
-0.6680746561	17	0.2%
Other values (6618)	10092	97.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.6946675877	1	< 0.1%
-0.6938728712	2	< 0.1%
-0.6936766737	1	< 0.1%
-0.6934098218	1	< 0.1%
-0.6930057484	3	< 0.1%
-0.6929596187	1	< 0.1%
-0.6929310066	1	< 0.1%
-0.6923173055	1	< 0.1%
-0.6922384762	1	< 0.1%
-0.6919085608	1	< 0.1%

Value	Count	Frequency (%)
16.21874812	1	< 0.1%
13.40156681	1	< 0.1%
10.66976058	2	< 0.1%
8.762609098	1	< 0.1%
8.748043188	13	0.1%
8.20241745	1	< 0.1%
7.88020749	1	< 0.1%
7.873445101	1	< 0.1%
7.477341686	1	< 0.1%
7.065030959	4	< 0.1%

Line Item Insurance (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	6936
Distinct (%)	67.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0

Minimum	-0.4795104774
Maximum	15.08883688
Zeros	0
Zeros (%)	0.0%
Negative	7675
Negative (%)	74.3%
Memory size	80.8 KiB

Quantile statistics

Minimum	-0.4795104774
5-th percentile	-0.4789853678
Q1	-0.46602425
median	-0.383910242
Q3	0.02536722052
95-th percentile	1.675204919
Maximum	15.08883688
Range	15.56834736
Interquartile range (IQR)	0.4913914705

Descriptive statistics

Standard deviation	1.000048434
Coefficient of variation (CV)	nan
Kurtosis	35.51248453
Mean	0
Median Absolute Deviation (MAD)	0.09391382577
Skewness	4.862276887
Sum	-5.684341886 × 10^-14
Variance	1.000096871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.4794902808	41	0.4%
-0.4795104774	36	0.3%
-0.4793892982	33	0.3%
-0.4794296913	31	0.3%
-0.4794094948	30	0.3%
-0.4793691017	25	0.2%
-0.4794700843	23	0.2%
-0.4793489052	21	0.2%
-0.4792883156	19	0.2%
-0.4785410443	19	0.2%
Other values (6926)	10046	97.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.4795104774	36	0.3%
-0.4795003791	2	< 0.1%
-0.4794902808	41	0.4%
-0.4794700843	23	0.2%
-0.4794498878	14	0.1%
-0.4794296913	31	0.3%
-0.4794094948	30	0.3%
-0.4793892982	33	0.3%
-0.4793691017	25	0.2%
-0.4793590035	1	< 0.1%

Value	Count	Frequency (%)
15.08883688	1	< 0.1%
13.66912239	1	< 0.1%
11.497451	1	< 0.1%
10.77661695	1	< 0.1%
10.5864061	1	< 0.1%
10.19239216	1	< 0.1%
10.08488608	1	< 0.1%
9.946499512	1	< 0.1%
9.911579726	2	< 0.1%
9.81685804	1	< 0.1%

Managed By_Ethiopia Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10323
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_Haiti Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10323
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_PMO - US
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	10265
0.0	59

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	10265	99.4%
0.0	59	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	10265	99.4%
0.0	59	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_South Africa Field Office
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10267
1.0	57

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10267	99.4%
1.0	57	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10267	99.4%
1.0	57	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_Direct Drop
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	5404
1.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	5404	52.3%
1.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	5404	52.3%
1.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	5404
0.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIF
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10321
1.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10321	> 99.9%
1.0	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10321	> 99.9%
1.0	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10049
1.0	275

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10049	97.3%
1.0	275	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10049	97.3%
1.0	275	2.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DAP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10315
1.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10315	99.9%
1.0	9	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10315	99.9%
1.0	9	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDP
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8881
1.0	1443

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8881	86.0%
1.0	1443	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8881	86.0%
1.0	1443	14.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDU
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10309
1.0	15

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10309	99.9%
1.0	15	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10309	99.9%
1.0	15	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_EXW
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7546
1.0	2778

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	7546	73.1%
1.0	2778	26.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7546	73.1%
1.0	2778	26.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_FCA
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9927
1.0	397

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9927	96.2%
1.0	397	3.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9927	96.2%
1.0	397	3.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_N/A - From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	5404
0.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	6113
0.0	4211

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	6113	59.2%
0.0	4211	40.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	6113	59.2%
0.0	4211	40.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air Charter
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9674
1.0	650

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9674	93.7%
1.0	650	6.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9674	93.7%
1.0	650	6.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Ocean
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9953
1.0	371

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9953	96.4%
1.0	371	3.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9953	96.4%
1.0	371	3.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Truck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7494
1.0	2830

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7494	72.6%
1.0	2830	27.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7494	72.6%
1.0	2830	27.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10308
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ANTM
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10302
1.0	22

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10302	99.8%
1.0	22	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10302	99.8%
1.0	22	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ARV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	8550
0.0	1774

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	8550	82.8%
0.0	1774	17.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	8550	82.8%
0.0	1774	17.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_HRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8596
1.0	1728

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8596	83.3%
1.0	1728	16.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8596	83.3%
1.0	1728	16.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_MRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10316
1.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10316	99.9%
1.0	8	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10316	99.9%
1.0	8	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10308
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Adult
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	6595
0.0	3729

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	6595	63.9%
0.0	3729	36.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	6595	63.9%
0.0	3729	36.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8757
1.0	1567

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8757	84.8%
1.0	1567	15.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8757	84.8%
1.0	1567	15.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test - Ancillary
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10163
1.0	161

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10163	98.4%
1.0	161	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10163	98.4%
1.0	161	1.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Malaria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10294
1.0	30

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10294	99.7%
1.0	30	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10294	99.7%
1.0	30	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Pediatric
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8369
1.0	1955

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8369	81.1%
1.0	1955	18.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8369	81.1%
1.0	1955	18.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_No
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7030
1.0	3294

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7030	68.1%
1.0	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7030	68.1%
1.0	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_Yes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	7030
0.0	3294

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	7030	68.1%
0.0	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	7030	68.1%
0.0	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_CIP	Vendor INCO Term_DDU	Vendor INCO Term_EXW	Vendor INCO Term_FCA	Shipment Mode_Air	Product Group_ARV	Product Group_HRDT	Sub Classification_Adult	Sub Classification_HIV test	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
0	-0.626709	-0.457457	-0.455085	0.154791	0.108859	-0.340033	-0.649146	-0.477986	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0
1	2.115663	-0.432952	-0.438724	-0.345104	-0.178113	-0.312457	-0.430691	-0.458446	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
2	0.287415	-0.445442	-0.340828	1.272978	0.056960	-0.327404	-0.598144	-0.351081	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0
3	-0.234942	0.339404	-0.087803	-0.393559	-0.165902	-0.192802	0.239975	-0.062392	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
4	-0.234942	0.491277	-0.104488	-0.410880	-0.172008	0.265596	1.959214	-0.056787	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
5	2.115663	-0.447540	-0.450235	-0.363741	-0.181166	-0.300787	-0.349006	-0.472179	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
6	0.156826	-0.454559	-0.444013	0.229337	-0.077368	-0.314855	-0.605485	-0.470361	1.0	1.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
7	-0.234942	-0.041604	-0.280485	-0.401014	-0.168955	-0.222935	-0.331956	-0.356231	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
8	-0.234942	-0.451112	-0.455139	-0.438287	-0.178113	-0.302785	-0.410859	-0.478268	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0
9	0.548593	-0.387990	-0.123372	0.420087	-0.083474	-0.289677	-0.130211	-0.107167	1.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0

Last rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_From RDC	Vendor INCO Term_N/A - From RDC	Shipment Mode_Air	Shipment Mode_Air Charter	Shipment Mode_Truck	Product Group_ARV	Sub Classification_Adult	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
10314	-0.234942	-0.199647	-0.348868	-0.402110	-0.168955	0.162087	0.294509	-0.402239	1.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0
10315	0.548593	1.290610	3.322444	-0.072354	-0.138426	0.873702	0.833994	2.229489	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
10316	-0.234942	-0.083244	-0.173421	-0.338088	-0.153690	-0.217420	-0.495594	-0.247049	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
10317	-0.626709	-0.289972	-0.395920	-0.412634	-0.156743	0.153134	2.066158	-0.429665	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0
10318	-0.234942	4.668867	1.683340	-0.402110	-0.168955	1.727512	1.997839	1.276880	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
10319	-0.234942	3.702873	1.280116	-0.402110	-0.168955	1.727512	1.997839	0.945920	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
10320	-0.234942	0.068430	-0.058757	-0.338088	-0.153690	0.012698	0.165692	-0.152933	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
10321	-0.626709	12.394498	14.430762	-0.262008	-0.086527	4.665133	3.192730	10.192392	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
10322	-0.234942	-0.021670	-0.126871	-0.338088	-0.153690	-0.229809	-0.480272	-0.208837	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0
10323	-0.234942	0.457280	-0.245505	-0.437410	-0.178113	0.709366	-0.013212	-0.306204	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0

Most frequently occurring

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_DDP	Vendor INCO Term_EXW	Shipment Mode_Air	Shipment Mode_Truck	Product Group_ARV	Product Group_HRDT	Sub Classification_Adult	Sub Classification_HIV test	Sub Classification_HIV test - Ancillary	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes	# duplicates
80	0.287415	-0.389389	0.250648	1.470305	0.084436	-0.246275	0.760840	0.211978	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	6
4	-1.005417	-0.383294	-0.244653	0.056128	7.292324	-0.181851	0.839035	-0.296631	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	5
99	2.899197	-0.457881	-0.456545	0.033106	-0.162849	-0.300347	-0.159322	-0.479409	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	1.0	5
94	2.115663	-0.457507	-0.456415	-0.362425	-0.181166	-0.328643	-0.353802	-0.479349	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	4
2	-1.005417	-0.456807	-0.456030	-0.371415	1.339176	-0.337954	-0.611779	-0.479006	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	1.0	3
5	-1.005417	-0.370255	-0.222861	0.023240	6.834390	-0.138450	0.478020	-0.159961	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	3
16	-0.626709	-0.457782	-0.456490	-0.239425	-0.074315	0.521011	0.583804	-0.479389	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	3
20	-0.626709	-0.457757	-0.456393	-0.169264	-0.043786	0.521011	0.043251	-0.479329	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	3
27	-0.626709	-0.457682	-0.456002	0.032887	0.050854	0.521611	0.066565	-0.479046	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	3
28	-0.626709	-0.457657	-0.455986	-0.002413	0.035589	0.521611	0.066565	-0.479026	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	3

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script